#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
namespace HeuristicLab.Encodings.LinearLinkageEncoding {
[Item("Split Group Manipulator", "Performs a maximum of N split operations on the groups. An already split group may be split again.")]
[StorableType("66661F32-5835-4D46-867C-CD96079DC7E6")]
public sealed class SplitGroupManipulator : LinearLinkageManipulator {
public IValueLookupParameter NParameter {
get { return (IValueLookupParameter)Parameters["N"]; }
}
[StorableConstructor]
private SplitGroupManipulator(bool deserializing) : base(deserializing) { }
private SplitGroupManipulator(SplitGroupManipulator original, Cloner cloner) : base(original, cloner) { }
public SplitGroupManipulator() {
Parameters.Add(new ValueLookupParameter("N", "The number of groups to split.", new IntValue(1)));
}
public SplitGroupManipulator(int n)
: this() {
NParameter.Value = new IntValue(n);
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SplitGroupManipulator(this, cloner);
}
public static void Apply(IRandom random, LinearLinkage lle, int n) {
var grouping = lle.GetGroups().ToList();
var groupsLargerOne = grouping.Select((v, i) => Tuple.Create(i, v))
.Where(x => x.Item2.Count > 1)
.ToDictionary(x => x.Item1, x => x.Item2);
if (groupsLargerOne.Count == 0) return;
var toRemove = new List();
for (var i = 0; i < n; i++) {
var g = groupsLargerOne.Keys.SampleRandom(random);
var idx = random.Next(1, groupsLargerOne[g].Count);
// shuffle here to avoid a potential bias of grouping smaller and larger numbers together
var tmp = groupsLargerOne[g].Shuffle(random);
var before = new List();
var after = new List();
foreach (var t in tmp) {
if (idx > 0) before.Add(t);
else after.Add(t);
idx--;
}
if (before.Count > 1) groupsLargerOne[grouping.Count] = before;
grouping.Add(before);
if (after.Count > 1) groupsLargerOne[grouping.Count] = after;
grouping.Add(after);
toRemove.Add(g);
groupsLargerOne.Remove(g);
if (groupsLargerOne.Count == 0) break;
}
foreach (var r in toRemove.OrderByDescending(x => x))
grouping.RemoveAt(r);
lle.SetGroups(grouping);
}
protected override void Manipulate(IRandom random, LinearLinkage lle) {
var N = NParameter.ActualValue.Value;
Apply(random, lle, N);
}
}
}